Continuous query processing of spatio-temporal data streams in PLACE

Abstract

The tremendous increase in the use of cellular phones, GPS-like devices, and RFIDs results in highly dynamic environments where objects as well as queries are continuously moving. In this paper, we present a continuous query processor designed specifically for highly dynamic environments (e.g., location-aware environments). We implemented the proposed continuous query processor inside the PLACE server (Pervasive Location-Aware Computing Environments); a scalable location-aware database server developed at Purdue University. The PLACE server extends data streaming management systems to support location-aware environments. These environments are characterized by the wide variety of continuous spatio-temporal queries and the unbounded spatio-temporal streams. The proposed continuous query processor includes: (1) New incremental spatio-temporal operators to support a wide variety of continuous spatio-temporal queries, (2) Extended semantics of sliding window queries to deal with spatial sliding windows as well as temporal sliding windows, and (3) A shared-execution framework for scalable execution of a set of concurrent continuous spatio-temporal queries. Experimental evaluation shows promising performance of the continuous query processor of the PLACE server.

abstract = "The tremendous increase in the use of cellular phones, GPS-like devices, and RFIDs results in highly dynamic environments where objects as well as queries are continuously moving. In this paper, we present a continuous query processor designed specifically for highly dynamic environments (e.g., location-aware environments). We implemented the proposed continuous query processor inside the PLACE server (Pervasive Location-Aware Computing Environments); a scalable location-aware database server developed at Purdue University. The PLACE server extends data streaming management systems to support location-aware environments. These environments are characterized by the wide variety of continuous spatio-temporal queries and the unbounded spatio-temporal streams. The proposed continuous query processor includes: (1) New incremental spatio-temporal operators to support a wide variety of continuous spatio-temporal queries, (2) Extended semantics of sliding window queries to deal with spatial sliding windows as well as temporal sliding windows, and (3) A shared-execution framework for scalable execution of a set of concurrent continuous spatio-temporal queries. Experimental evaluation shows promising performance of the continuous query processor of the PLACE server.",

N2 - The tremendous increase in the use of cellular phones, GPS-like devices, and RFIDs results in highly dynamic environments where objects as well as queries are continuously moving. In this paper, we present a continuous query processor designed specifically for highly dynamic environments (e.g., location-aware environments). We implemented the proposed continuous query processor inside the PLACE server (Pervasive Location-Aware Computing Environments); a scalable location-aware database server developed at Purdue University. The PLACE server extends data streaming management systems to support location-aware environments. These environments are characterized by the wide variety of continuous spatio-temporal queries and the unbounded spatio-temporal streams. The proposed continuous query processor includes: (1) New incremental spatio-temporal operators to support a wide variety of continuous spatio-temporal queries, (2) Extended semantics of sliding window queries to deal with spatial sliding windows as well as temporal sliding windows, and (3) A shared-execution framework for scalable execution of a set of concurrent continuous spatio-temporal queries. Experimental evaluation shows promising performance of the continuous query processor of the PLACE server.

AB - The tremendous increase in the use of cellular phones, GPS-like devices, and RFIDs results in highly dynamic environments where objects as well as queries are continuously moving. In this paper, we present a continuous query processor designed specifically for highly dynamic environments (e.g., location-aware environments). We implemented the proposed continuous query processor inside the PLACE server (Pervasive Location-Aware Computing Environments); a scalable location-aware database server developed at Purdue University. The PLACE server extends data streaming management systems to support location-aware environments. These environments are characterized by the wide variety of continuous spatio-temporal queries and the unbounded spatio-temporal streams. The proposed continuous query processor includes: (1) New incremental spatio-temporal operators to support a wide variety of continuous spatio-temporal queries, (2) Extended semantics of sliding window queries to deal with spatial sliding windows as well as temporal sliding windows, and (3) A shared-execution framework for scalable execution of a set of concurrent continuous spatio-temporal queries. Experimental evaluation shows promising performance of the continuous query processor of the PLACE server.